2016 INFORMS Annual Meeting Program

MD60

INFORMS Nashville – 2016

4 - Optimal Process Adaptation For Robust Iot Collaboration Zhe Shan, University of Cincinnati, Cincinnati, OH, Contact: zhe.shan@uc.edu The purpose of process adaptation is to mediate the communication between sev- eral independent IoT processes to overcome their mismatches and incompatibili- ties. In this work, we propose a new framework and efficient algorithms for cre- ating optimal adapters for IoT process collaboration. This solution integrates mes- sage adaptation patterns with control flow adapters to create a complete adapter for multiple processes. The comparisons against existing methods show that our approach produces remarkable improvements. MD57 Music Row 5- Omni Influencing Behavior in Aircraft Operations Sponsored: Behavioral Operations Management Sponsored Session Chair: Kenneth Schultz, Air Force Institute of Technology, 2950 Hobson Way, WPAFB, OH, 45433, United States, kschultz@afit.edu 1 - Antecedents Of Fuel Efficiency James Cotton, AFIT, James.cotton@afit.edu The United States Air Force (USAF) uses $15B of fuel each year, more than all other Department of Defense agencies combined (USAF 2014, 30). USAF data show that certain pilots fly more efficiently than their peers; however, current literature has little research on discretionary pro-environmental professional behaviors. We use the Theory of Planned Behavior as a starting point (Ajzen, 1985, 2011), and incorporate theory as proposed by Lülfs and Hahn (2013, 2014) and McDonald (2014), including additional factors to more accurately capture the behavior and context of USAF cargo pilots. The results should help us understand pilot motivation and help us encourage more efficient vehicle operation. 2 - The Effects Of Public Versus Private Feedback On Autonomous Motivation Kenneth Schultz, Air Force Institute of Technology, WPAFB, OH, Kenneth.Schultz@afit.edu, Cory Sanders Research has shown public feedback increases work performance compared to private feedback (Song, Tucker, Murrell, and Vinson, 2015). What motivates employees to perform differently in the two conditions is an open question. To answer this, we can investigate the motivation type differential between the two (Ryan and Deci, 2000). Motivation type is important because controlled motiva- tion can result in unethical behavior (Welsh and Ordonez, 2014), lower quality of life (Gagne, 2014), and lower task persistence (Ryan and Deci, 2000) com- pared to autonomous motivation. We will investigate this question in a longitu- dinal field experiment using Boeing C-17 pilots’ fuel efficiency performance. MD58 Music Row 6- Omni Energy VIII Contributed Session Chair: Carlos Abreu, Adjunct Professor, Federal University of Rio Grande do Norte State (UFRN), Natal, Brazil, calexandreabreu@ect.ufrn.br 1 - Optimal Multi-Period Energy Procurement Policies With The Integration Of Wind Energy Tian Wang, Huazhong University of Science and Technology, School of Management, Hongshan Distrct, Wuhan, 430074, China, wangtian3261@gmail.com The changes of electricity market are envisioned to be revolutionary in power generation and consumption. How to manage the increasing potential of adjustable demand with the increasing penetration of renewable sources is one of the most significant problems. We investigate a multi-period energy procurement model for a smart grid community. Multiple periods of harvesting (renewable energy) and purchasing (traditional energy) are required for satisfying demand. Demand can be delayed if any energy shortfall. At the end, all demand must be fulfilled. We obtain dynamic solutions and provide numerical studies.

2 - Energy Flow Network Stochastic Optimization Through Predictive Analytics Of Energy Demand Ebisa Wollega, Assistant Professor, Colorado State University- Pueblo, 2200 Bonforte Blvd, Pueblo, CO, 81001, United States, ebisa.wollega@csupueblo.edu, Hiba Baroud, Vitor Winckler Modeling energy flow depends on a number of uncertain factors that are related to economic development, extreme weather, and renewable energy sources availability, among many others. In order to improve decision making under uncertainty in the energy sector, we present a stochastic non-linear mixed integer energy flow network model under supply uncertainty where the energy demand is determined through data-driven statistical models. Computational results that compare the performance of different predictive models for energy demand and the efficiency of the solution approach will be presented. 3 - Real Time Pricing Strategies And Dynamic Load Scheduling In Smart Communities Vignesh Subramanian, University of South Florida, 5006, Bordeaux Village pl, Apt #201, Tampa, FL, 33617, United States, vigneshs@mail.usf.edu, Tapas K. Das Real Time pricing will actively engage the electricity consumers, having an advanced metering infrastructure (AMI), in a centralized demand side management (CDSM), a key to price stability and network reliability. We propose a Quadratic Binary Programming model for a centralized controller to schedule the consumer load. The numerical result demonstrates how CDSM can lower the price peaks, reduce the reserve capacity of the generator and minimize the consumer’s hourly tariff. 4 - The Effects Of Low Prices And Higher Uncertainty On Enhanced Oil Recovery Projects: A Real Options Valuation Perspective Carlos Abreu, Adjunct Professor, Federal University of Rio Grande do Norte State (UFRN), Natal, Brazil, calexandreabreu@ect.ufrn.br, Lielson Santos, Juli Sergine, Nayara Nagly Real Option Valuation main objective is the financial analysis of projects under uncertainty conditions. The Oil and Gas industry is full of uncertainties starting with its main economic variable, oil prices. Using a Real Options model to evaluate the potential return of an oil project captures the flexibility of a decision- maker to capture possible prices oscillations. Enhanced oil recovery projects are developed to try to elevate mature oil field production using injection technology. We focus on the injection of natural gas to boost the oil production analyzing uncertainty scenarios involving oil and gas markets to estimate a decision - making rule for investment in a Real Option perspective. MD60 Cumberland 2- Omni Modeling and Analysis of Innovative Mobility Services I Sponsored: TSL, Urban Transportation Sponsored Session Chair: Yafeng Yin, University of Florida, University of Florida, Gainesville, FL, 32611, United States, yafeng@ce.ufl.edu 1 - A Stable Matching Paradigm For Transport Service Allocation, User Assignment, And Pricing Joseph Y J Chow, New York University, joseph.chow@nyu.edu Assignment in a generic transportation system (including shared mobility options) is modeled as a many-to-one stable matching problem of passengers to tour sets. The result allows joint assignment of flows and mechanism design for allocation of costs, with implications for designing fare pricing and incentives for shared mobility, and designing for partnerships between operators in this setting. 2 - Modeling Surge Pricing In Ride Sourcing Markets Yafeng Yin, University of Florida, Civil and Coastal Engineering, 365 Weil Hall Box 116580, Gainesville, FL, 32611, United States, yafeng@ce.ufl.edu, Liteng Zha This study proposes an equilibrium model to quantitatively investigate the effects of surge pricing on the ride-sourcing market (e.g., Uber and Lyft). The proposed model explicitly captures the behaviors of agents at both demand and supply sides. Equilibrium outcomes under surging strategies with different control objectives are compared and discussed. 3 - Is Ride-sourcing Services Worsening Traffic Congestion? Hongyu Chen, Northwestern University, chyy1989@gmail.com, Yu Nie Ride-sourcing services which allow private car owners to provide taxi-like services for profit, have offered passengers a convenient choice of transportation but also created controversies. It has been argued that they might have worsened traffic congestion by both attracting more demand for mobility services and inducing more empty-loaded vehicles on the road network. This research aims to analyze the personal mobility services market with both traditional taxi and ride- sourcing services using an aggregate economic model. Various impacts of the emerging services on the market, especially on traffic congestion, will be the focus of this research.

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